PR - Historic Residual Returns To Farm Land, Labour And Management, Saskatchewan: 1926-2005
Bibliographic record
Abstract
One of the more enduring and useful farm business management benchmarks has been the “Residual Return to Land, Labour and Management†(RLLM). Historically, it has been used as a return to the two residual claimants –farmland and family labour and management. It also can be used as a starting point for several other benchmarks. Two measures of RLLM are examined, one based on regional farm level data (microdata approach) and the other based on provincial income and expense statistics (the aggregate approach). While they result in similar 1926-1999 means, they result in somewhat different patterns because of the differing relative impacts of drought and new crops such as canola. Nevertheless, they both show the narrowing margin of the residual, particularly after 1980. Cost shares are also used to delineate a series of agricultural epochs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".